code: def get_feats(self, loc):
      x = self.read_audio(loc)
      with torch.no_grad():
          source = torch.from_numpy(x).float().cuda()
          if self.task.cfg.normalize:
              assert source.dim() == 1, source.dim()
              with torch.no_grad():
                  source = F.layer_norm(source, source.shape)
          source = source.view(1, -1)
  
          m_res = self.model(
              source=source,
              mask=False,
              features_only=True,
              layer=self.layer,
          )
          return m_res["x"].squeeze(0).cpu()
  
file_path: fairseq/examples/wav2vec/unsupervised/scripts/wav2vec_extract_features.py
imports: import argparse
  import os
  import os.path
  import tqdm
  import torch
  import torch.nn.functional
  from shutil import copyfile
  from npy_append_array import NpyAppendArray
  import fairseq
  import soundfile
label_desc: Use image node_id 3 for calling the Wav2VecFeatureReader obj's underlying member method code with example usage: obj.get_feats(loc) and returns: m_res